@inproceedings{495dcf86ea8d45be8e9626cc8d09fcfb,
title = "Analysis of Deep Learning Libraries: Keras, PyTorch, and MXnet",
abstract = "As many artificial neural libraries are developing the deep learning algorithm and implementing it became accessible to anyone. This study points out the disparity of performance in deep learning models such as convolutional neural networks (CNN) when implemented with different artificial neural libraries. Libraries such as Keras, Pytorch, and MXnet was utilized for each three CNN model then binary image classification was done based on the Dogs vs. Cats dataset from Kaggle. With using 75\% of the dataset as the training set and the rest of 25\% as a testing set, and as a result, each CNN model gave a different F1 score value and accuracy.",
keywords = "artificial neural network, Binary image classification, CNN, Keras, MXnet, Pytorch",
author = "Seongsoo Kim and Hayden Wimmer and Jongyeop Kim",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 20th IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, SERA 2022 ; Conference date: 25-05-2022 Through 27-05-2022",
year = "2022",
month = jun,
day = "30",
doi = "10.1109/SERA54885.2022.9806734",
language = "English",
isbn = "9781665483506",
series = "2022 IEEE/ACIS 20th International Conference on Software Engineering Research, Management and Applications, SERA 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "54--62",
editor = "Juyeon Jo and Yeong-Tae Song and Lin Deng and Junghwan Rhee",
booktitle = "2022 IEEE/ACIS 20th International Conference on Software Engineering Research, Management and Applications, SERA 2022",
address = "United States",
}